Software QA Specialist

Have you heard of BlueCat? We’re one of those hidden gems that’s been disrupting the market as a key player in the rapidly growing space of Intelligent Network Operations. Organizations require a new model of network operations that links foundational core services with a deep, predictive understanding of network health and performance to improve change readiness. BlueCat’s Intelligent NetOps is a first-to-market combination of systems of understanding and change. BlueCat enables teams to enhance agility and mitigate risks from high rates of change with a unified management lifecycle, from provisioning to proactive troubleshooting and remediation.

At BlueCat, we take immense pride in our award-winning culture, an integral part of our identity. We are proud recipients of several prestigious accolades, including the "Great Place to Work" certification. By becoming a part of our team, you not only join a company at the forefront of technology but also become an integral member of Canada's top workplaces in various categories, including Technology, Today's Youth and Women, and Mental Health and Inclusion.

We are seeking a skilled Software QA Specialist with strong expertise in Python automation, performance / scalability testing and Kubernetes.

In this role, you will design, implement, and manage end-to-end API integration tests in Python, to ensure our products meet the highest standards of quality and scalability. 
You will play a key role as a gatekeeper of product quality, enabling the delivery of robust, enterprise-grade networking software solutions.
 
Responsibilities:
•    Develop and execute test strategies covering functional, regression, integration, performance, and scalability testing.
•    Design and automate API and system-level test cases using Python/Pytest, integrated into CI/CD pipelines.
•    Build and manage Kubernetes-based test environments to validate performance at scale.
•    Conduct and analyze performance/load testing using observability tools (e.g., Grafana).
•    Validate systems involving data platforms (e.g., data lakes, ClickHouse) ensuring data integrity, performance, and reliability.
•    Participate in testing of AI-driven systems, including agentic AI workflows, ensuring correctness, robustness, and scalability.
•    Track and manage test coverage, results, and defects in Jira.
•    Collaborate with engineering and product teams to ensure requirements are testable and products are release-ready.
•    Continuously research and recommend new testing tools, frameworks, and approaches.

Qualifications:
•    Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).
•    Strong Python automation skills with Pytest, including API and backend testing.
•    Hands-on experience with Kubernetes in testing or production environments.
•    Proven experience with performance and scalability testing in distributed systems.
•    Familiarity with CI/CD workflows (e.g., GitLab).
•    Strong analytical, problem-solving, and communication skills.
 
Nice-to-Have:
•    Experience with cloud platforms (AWS, Azure, GCP).
•    Hands-on with performance/load testing tools (Locust, JMeter, k6).
•    Experience with AI/ML system testing, including validation of agentic or autonomous workflows.
•    Experience with UI automation (Playwright, Selenium).
•    Familiarity with VMware or other virtualization technologies.
•    Experience testing data-intensive systems (e.g., data lakes, analytical databases like ClickHouse or similar).
•    Solid understanding of networking concepts/protocols.
•    Professional certifications (CCNA, ISTQB, etc.).
 
What We’re Looking For:
We’re looking for a person who can step up and take ownership of quality at scale, bringing strong expertise in Python automation, Kubernetes, distributed systems, and modern data platforms.
Experience or genuine interest in AI system testing, including agentic AI workflows, is highly valued.
You are detail-oriented, proactive, and collaborative, with the ability to drive quality initiatives and deliver results in complex, data-driven environments.